We are seeking a visionary, results-oriented Director of Enterprise AI Strategy & Transformation to define and execute our enterprise-wide Artificial Intelligence roadmap.

In this executive role, you will bridge the gap between business strategy, technological capability, and operational execution. You will partner directly with C-suite stakeholders, business unit heads, and engineering teams to identify high-impact AI opportunities, modernize operating models, institute responsible AI governance, and accelerate value realization across the enterprise.

Key Responsibilities

Strategic Vision & AI Roadmapping

• Define the overarching Enterprise AI Vision, aligning investments in Generative AI, predictive analytics, and machine learning with core business outcomes.

• Identify, evaluate, and prioritize AI use cases across commercial, operational, and customer-facing domains based on ROI, technical feasibility, and strategic leverage.

• Establish metrics and KPIs to measure AI adoption, operational efficiencies, and bottom-line business value.

Operating Model & Change Enablement

• Architect an agile AI operating model (e.g., Hub-and-Spoke / AI Center of Excellence) to scale capabilities across disparate business units.

• Spearhead organization-wide change management, leading AI literacy and upskilling programs to build a data- and AI-fluent culture.

• Partner with Product, IT, and Data Engineering teams to ensure alignment on infrastructure, modern data stacks, and model lifecycle management (MLOps).

Governance, Risk & Responsible AI

• Establish enterprise Responsible AI (RAI) frameworks addressing data privacy, bias mitigation, model explainability, security, and regulatory compliance.

• Lead the cross-functional AI Governance Council to evaluate third-party AI vendors, foundation models, and custom deployment risks.

Required Qualifications

• Experience: 12+ years of progressive leadership experience in enterprise strategy, management consulting, or digital transformation, with at least 5+ years dedicated to AI/ML strategy and deployment.

• Track Record: Demonstrated success leading large-scale AI transformation programs from ideation through production deployment with measurable P&L or efficiency impact.

• Executive Presence: Exceptional communication skills with the ability to translate complex AI/technical concepts into actionable business strategies for executive stakeholders and board members.

• Technical Acumen: Strong functional understanding of the modern AI landscape, including LLMs, generative architectures, agentic workflows, MLOps, and cloud ecosystems (AWS, Azure, or GCP).

• Education: Bachelor’s degree in Business, Computer Science, Data Science, Engineering, or a related field (Master’s or MBA preferred).

Preferred Qualifications

• Experience orchestrating enterprise AI transformation within heavily regulated industries (e.g., Financial Services, Healthcare/Life Sciences, or Manufacturing).

• Active engagement with global AI governance standards, frameworks (e.g., NIST AI RMF, ISO 42001), and emerging regulatory policies.

Trazup builds AI software whose outputs can be checked and traced back to source. Our products are Guido (a workspace for interviews, analysis, planning, and reports), Upstride (two-sided hiring and onboarding), and Groundtruth (turns customer conversations into a price and a business case). We sell into retail, healthcare, supply chain, and banking and financial services, where buyers care as much about how an answer was produced as what the answer is.

This is our first dedicated sales hire. You will own the full cycle: build the pipeline, run the deals, close them, and turn what you learn in the market into how we position and price. You will do this hands-on before you build a team, and you will report directly to the CEO.

What You Will Own

Pipeline and Revenue

• Own the number. Build and close a pipeline of mid-market and enterprise deals across our four target industries.
• Prospect directly. Outbound, network, events, and partner referrals, not just inbound.
• Run the full cycle from first conversation through security review, procurement, and signature.
• Land and expand. Convert pilots and paid proofs of concept into production contracts.

Positioning and Go To Market

• Translate our traceability and verifiability story into language a business buyer acts on.
• Build the repeatable pieces: qualification criteria, discovery questions, demo flow, pricing guardrails, objection handling, and proposal templates.
• Bring the market back to the team. Feed win and loss patterns into product priorities and roadmap decisions.
• Identify and develop channel and partner relationships that shorten the path to a first deal.

Deal Execution in Regulated Buying Environments

• Navigate procurement, legal, security, and risk reviews common in healthcare and financial services.
• Work with the technical team to scope pilots that prove value fast and lead somewhere.
• Keep a clean, current forecast the leadership team can plan against.

Team, Later

• Define the sales process well enough that the second and third hires can run it.
• Hire and coach the first reps once the motion is proven.

Required Qualifications

• 8+ years in B2B software sales, with at least 3 years selling technical or data-heavy products to director and VP level buyers.
• Consistent record of carrying and hitting a quota, with deal sizes and cycles you can speak to in detail.
• Proven outbound builder. You have created pipeline from a standing start, not just worked leads handed to you.
• Comfortable selling early-stage products where the roadmap is part of the conversation and not everything is built yet.
• Credible in a technical discussion. You can hold your own on AI, data, and integration questions without a solutions engineer in the room.
• Strong written communication. You will write the proposals, not review someone else's.

Preferred Qualifications

• Experience selling into retail, healthcare, supply chain, or financial services.
• Familiarity with how enterprises evaluate AI vendors, including model risk, data handling, and governance reviews.
• Prior first or early sales hire at a startup.
• Experience selling in the HR technology, analytics, or pricing and quoting categories.